{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dogs vs Cats 识别\n",
    "\n",
    "\n",
    "## 使用 Kaggle 的数据集\n",
    "\n",
    "**原始数据：**\n",
    "\n",
    " * 12500 dogs + 12500 cats 训练集\n",
    " \n",
    " * 12500 未标识测试集\n",
    " \n",
    "**转换：**\n",
    "\n",
    " * 1000 dogs + 1000 cats 训练集\n",
    " * 1000 dogs + 1000 cats 验证集\n",
    " * 500 dogs + 500 cats 测试集\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, shutil\n",
    "\n",
    "# 创建相关的路径\n",
    "original_dataset_dir = '/Users/haoxingxiao/academic/data/dogs-vs-cats/train'\n",
    "base_dir = '/Users/haoxingxiao/academic/data/dogs-vs-cats/small'\n",
    "\n",
    "train_dir = os.path.join(base_dir, 'train')\n",
    "validation_dir = os.path.join(base_dir, 'validation')\n",
    "test_dir = os.path.join(base_dir, 'test')\n",
    "\n",
    "train_cats_dir = os.path.join(train_dir, 'cats')\n",
    "train_dogs_dir = os.path.join(train_dir, 'dogs')\n",
    "validation_cats_dir = os.path.join(validation_dir, 'cats')\n",
    "validation_dogs_dir  = os.path.join(validation_dir, 'dogs')\n",
    "test_cats_dir = os.path.join(test_dir, 'cats')\n",
    "test_dogs_dir = os.path.join(test_dir, 'dogs')\n",
    "\n",
    "# 猫测试集\n",
    "fnames = ['cat.{}.jpg'.format(i) for i in range(1000)]\n",
    "for fname in fnames:\n",
    "    src = os.path.join(original_dataset_dir, fname)\n",
    "    dst = os.path.join(train_cats_dir, fname)\n",
    "    shutil.copyfile(src, dst)\n",
    "\n",
    "# 猫验证集\n",
    "fnames = ['cat.{}.jpg'.format(i) for i in range(1000, 1500)]\n",
    "for fname in fnames:\n",
    "    src = os.path.join(original_dataset_dir, fname)\n",
    "    dst = os.path.join(validation_cats_dir, fname)\n",
    "    shutil.copyfile(src, dst)\n",
    "    \n",
    "# 猫测试集\n",
    "fnames = ['cat.{}.jpg'.format(i) for i in range(1500, 2000)]\n",
    "for fname in fnames:\n",
    "    src = os.path.join(original_dataset_dir, fname)\n",
    "    dst = os.path.join(test_cats_dir, fname)\n",
    "    shutil.copyfile(src, dst)\n",
    "    \n",
    "# 狗测试集\n",
    "fnames = ['dog.{}.jpg'.format(i) for i in range(1000)]\n",
    "for fname in fnames:\n",
    "    src = os.path.join(original_dataset_dir, fname)\n",
    "    dst = os.path.join(train_dogs_dir, fname)\n",
    "    shutil.copyfile(src, dst)\n",
    "\n",
    "# 狗验证集\n",
    "fnames = ['dog.{}.jpg'.format(i) for i in range(1000, 1500)]\n",
    "for fname in fnames:\n",
    "    src = os.path.join(original_dataset_dir, fname)\n",
    "    dst = os.path.join(validation_dogs_dir, fname)\n",
    "    shutil.copyfile(src, dst)\n",
    "    \n",
    "# 狗测试集\n",
    "fnames = ['dog.{}.jpg'.format(i) for i in range(1500, 2000)]\n",
    "for fname in fnames:\n",
    "    src = os.path.join(original_dataset_dir, fname)\n",
    "    dst = os.path.join(test_dogs_dir, fname)\n",
    "    shutil.copyfile(src, dst)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total training cat images: 1000\n",
      "total training dog images: 1000\n",
      "total validation cat images: 500\n",
      "total validation dog images: 500\n",
      "total test cat images: 500\n",
      "total test dog images: 500\n"
     ]
    }
   ],
   "source": [
    "print('total training cat images:', len(os.listdir(train_cats_dir)))\n",
    "print('total training dog images:', len(os.listdir(train_dogs_dir)))\n",
    "print('total validation cat images:', len(os.listdir(validation_cats_dir)))\n",
    "print('total validation dog images:', len(os.listdir(validation_dogs_dir)))\n",
    "print('total test cat images:', len(os.listdir(test_cats_dir)))\n",
    "print('total test dog images:', len(os.listdir(test_dogs_dir)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "已经构建好了数据集。\n",
    "回忆MNIST数据集上的训练，这里复用：使用卷积层 Conv2D + relu 激活和 maxPooling2D 层交替。\n",
    "这里设定：输入 150*150， 输出到 Flatten 层是 7*7。\n",
    "\n",
    "**卷积神经网络模式的特点：深度不断增加，特征的尺寸逐渐减少**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras import layers\n",
    "from keras import models\n",
    "\n",
    "model = models.Sequential()\n",
    "model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(150, 150, 3)))\n",
    "model.add(layers.MaxPooling2D((2, 2)))\n",
    "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
    "model.add(layers.MaxPooling2D((2, 2)))\n",
    "model.add(layers.Conv2D(128, (3, 3), activation='relu'))\n",
    "model.add(layers.MaxPooling2D((2, 2)))\n",
    "model.add(layers.Conv2D(128, (3, 3), activation='relu'))\n",
    "model.add(layers.MaxPooling2D((2, 2)))\n",
    "model.add(layers.Flatten())\n",
    "model.add(layers.Dense(512, activation='relu'))\n",
    "model.add(layers.Dense(1, activation='sigmoid'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "看一下模型的变化："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_7 (Conv2D)            (None, 148, 148, 32)      896       \n",
      "_________________________________________________________________\n",
      "max_pooling2d_6 (MaxPooling2 (None, 74, 74, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_8 (Conv2D)            (None, 72, 72, 64)        18496     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_7 (MaxPooling2 (None, 36, 36, 64)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_9 (Conv2D)            (None, 34, 34, 128)       73856     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_8 (MaxPooling2 (None, 17, 17, 128)       0         \n",
      "_________________________________________________________________\n",
      "conv2d_10 (Conv2D)           (None, 15, 15, 128)       147584    \n",
      "_________________________________________________________________\n",
      "max_pooling2d_9 (MaxPooling2 (None, 7, 7, 128)         0         \n",
      "_________________________________________________________________\n",
      "flatten_2 (Flatten)          (None, 6272)              0         \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, 512)               3211776   \n",
      "_________________________________________________________________\n",
      "dense_4 (Dense)              (None, 1)                 513       \n",
      "=================================================================\n",
      "Total params: 3,453,121\n",
      "Trainable params: 3,453,121\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "配置网络用于训练："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras import optimizers\n",
    "\n",
    "model.compile(loss='binary_crossentropy',\n",
    "             optimizer=optimizers.RMSprop(lr=1e-4),\n",
    "             metrics=['acc'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 图像预处理\n",
    "\n",
    "需要将150*150的图像转换成\\[0, 0\\]区间内的张量。Keras有对应的图像处理库。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 2000 images belonging to 2 classes.\n",
      "Found 1000 images belonging to 2 classes.\n"
     ]
    }
   ],
   "source": [
    "from keras.preprocessing.image import ImageDataGenerator\n",
    "\n",
    "train_datagen = ImageDataGenerator(rescale = 1./255)\n",
    "test_datagen = ImageDataGenerator(rescale=1./255)\n",
    "\n",
    "train_generator = train_datagen.flow_from_directory(\n",
    "    train_dir,\n",
    "    target_size=(150, 150),\n",
    "    batch_size=20,\n",
    "    class_mode='binary')\n",
    "\n",
    "validation_generator = test_datagen.flow_from_directory(\n",
    "    validation_dir,\n",
    "    target_size=(150, 150),\n",
    "    batch_size=20,\n",
    "    class_mode='binary')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> 这里获得的是生成器结果，Keras提供了对这种输入类型的支持。每次会输出20个样本，因此需要提供batch_number作为终止输入的时刻。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_7 (Conv2D)            (None, 148, 148, 32)      896       \n",
      "_________________________________________________________________\n",
      "max_pooling2d_6 (MaxPooling2 (None, 74, 74, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_8 (Conv2D)            (None, 72, 72, 64)        18496     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_7 (MaxPooling2 (None, 36, 36, 64)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_9 (Conv2D)            (None, 34, 34, 128)       73856     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_8 (MaxPooling2 (None, 17, 17, 128)       0         \n",
      "_________________________________________________________________\n",
      "conv2d_10 (Conv2D)           (None, 15, 15, 128)       147584    \n",
      "_________________________________________________________________\n",
      "max_pooling2d_9 (MaxPooling2 (None, 7, 7, 128)         0         \n",
      "_________________________________________________________________\n",
      "flatten_2 (Flatten)          (None, 6272)              0         \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, 512)               3211776   \n",
      "_________________________________________________________________\n",
      "dense_4 (Dense)              (None, 1)                 513       \n",
      "=================================================================\n",
      "Total params: 3,453,121\n",
      "Trainable params: 3,453,121\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/30\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:158: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead.\n",
      "\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:163: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.\n",
      "\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:172: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.\n",
      "\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:180: The name tf.is_variable_initialized is deprecated. Please use tf.compat.v1.is_variable_initialized instead.\n",
      "\n",
      "WARNING:tensorflow:From /usr/local/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:187: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.\n",
      "\n",
      "100/100 [==============================] - 34s 340ms/step - loss: 0.6894 - acc: 0.5355 - val_loss: 0.6713 - val_acc: 0.5890\n",
      "Epoch 2/30\n",
      "100/100 [==============================] - 34s 338ms/step - loss: 0.6497 - acc: 0.6330 - val_loss: 0.6382 - val_acc: 0.6370\n",
      "Epoch 3/30\n",
      "100/100 [==============================] - 35s 347ms/step - loss: 0.6080 - acc: 0.6730 - val_loss: 0.6387 - val_acc: 0.6220\n",
      "Epoch 4/30\n",
      "100/100 [==============================] - 34s 338ms/step - loss: 0.5778 - acc: 0.6895 - val_loss: 0.5898 - val_acc: 0.6850\n",
      "Epoch 5/30\n",
      "100/100 [==============================] - 33s 331ms/step - loss: 0.5464 - acc: 0.7255 - val_loss: 0.5788 - val_acc: 0.7000\n",
      "Epoch 6/30\n",
      "100/100 [==============================] - 34s 340ms/step - loss: 0.5281 - acc: 0.7370 - val_loss: 0.5802 - val_acc: 0.6850\n",
      "Epoch 7/30\n",
      "100/100 [==============================] - 33s 326ms/step - loss: 0.4899 - acc: 0.7660 - val_loss: 0.5664 - val_acc: 0.6890\n",
      "Epoch 8/30\n",
      "100/100 [==============================] - 33s 331ms/step - loss: 0.4699 - acc: 0.7760 - val_loss: 0.5711 - val_acc: 0.7150\n",
      "Epoch 9/30\n",
      "100/100 [==============================] - 33s 333ms/step - loss: 0.4450 - acc: 0.7885 - val_loss: 0.5911 - val_acc: 0.6980\n",
      "Epoch 10/30\n",
      "100/100 [==============================] - 34s 338ms/step - loss: 0.4148 - acc: 0.8050 - val_loss: 0.5749 - val_acc: 0.7130\n",
      "Epoch 11/30\n",
      "100/100 [==============================] - 34s 340ms/step - loss: 0.3966 - acc: 0.8225 - val_loss: 0.5394 - val_acc: 0.7310\n",
      "Epoch 12/30\n",
      "100/100 [==============================] - 37s 374ms/step - loss: 0.3752 - acc: 0.8330 - val_loss: 0.6768 - val_acc: 0.6790\n",
      "Epoch 13/30\n",
      "100/100 [==============================] - 40s 405ms/step - loss: 0.3457 - acc: 0.8465 - val_loss: 0.5658 - val_acc: 0.7220\n",
      "Epoch 14/30\n",
      "100/100 [==============================] - 36s 359ms/step - loss: 0.3128 - acc: 0.8755 - val_loss: 0.5971 - val_acc: 0.7210\n",
      "Epoch 15/30\n",
      "100/100 [==============================] - 36s 359ms/step - loss: 0.3036 - acc: 0.8685 - val_loss: 0.5919 - val_acc: 0.7170\n",
      "Epoch 16/30\n",
      "100/100 [==============================] - 37s 366ms/step - loss: 0.2732 - acc: 0.8930 - val_loss: 0.6417 - val_acc: 0.7240\n",
      "Epoch 17/30\n",
      "100/100 [==============================] - 39s 388ms/step - loss: 0.2532 - acc: 0.9020 - val_loss: 0.6075 - val_acc: 0.7370\n",
      "Epoch 18/30\n",
      "100/100 [==============================] - 37s 372ms/step - loss: 0.2323 - acc: 0.9055 - val_loss: 0.7450 - val_acc: 0.6920\n",
      "Epoch 19/30\n",
      "100/100 [==============================] - 41s 407ms/step - loss: 0.2097 - acc: 0.9230 - val_loss: 0.6279 - val_acc: 0.7290\n",
      "Epoch 20/30\n",
      "100/100 [==============================] - 36s 357ms/step - loss: 0.1934 - acc: 0.9265 - val_loss: 0.7026 - val_acc: 0.7150\n",
      "Epoch 21/30\n",
      "100/100 [==============================] - 38s 380ms/step - loss: 0.1779 - acc: 0.9375 - val_loss: 0.6939 - val_acc: 0.7230\n",
      "Epoch 22/30\n",
      "100/100 [==============================] - 44s 436ms/step - loss: 0.1552 - acc: 0.9455 - val_loss: 0.7197 - val_acc: 0.7360\n",
      "Epoch 23/30\n",
      "100/100 [==============================] - 40s 404ms/step - loss: 0.1331 - acc: 0.9570 - val_loss: 0.8307 - val_acc: 0.7150\n",
      "Epoch 24/30\n",
      "100/100 [==============================] - 38s 381ms/step - loss: 0.1195 - acc: 0.9605 - val_loss: 0.7911 - val_acc: 0.7220\n",
      "Epoch 25/30\n",
      "100/100 [==============================] - 38s 380ms/step - loss: 0.1098 - acc: 0.9625 - val_loss: 0.9118 - val_acc: 0.6940\n",
      "Epoch 26/30\n",
      "100/100 [==============================] - 40s 397ms/step - loss: 0.0882 - acc: 0.9775 - val_loss: 0.9146 - val_acc: 0.7170\n",
      "Epoch 27/30\n",
      "100/100 [==============================] - 37s 367ms/step - loss: 0.0782 - acc: 0.9785 - val_loss: 0.8452 - val_acc: 0.7310\n",
      "Epoch 28/30\n",
      "100/100 [==============================] - 40s 398ms/step - loss: 0.0667 - acc: 0.9785 - val_loss: 0.9001 - val_acc: 0.7310\n",
      "Epoch 29/30\n",
      "100/100 [==============================] - 45s 448ms/step - loss: 0.0555 - acc: 0.9865 - val_loss: 1.0222 - val_acc: 0.7170\n",
      "Epoch 30/30\n",
      "100/100 [==============================] - 40s 402ms/step - loss: 0.0496 - acc: 0.9880 - val_loss: 0.9919 - val_acc: 0.7330\n"
     ]
    }
   ],
   "source": [
    "history = model.fit_generator(\n",
    "train_generator,\n",
    "steps_per_epoch=100,\n",
    "epochs=30,\n",
    "validation_data=validation_generator,\n",
    "validation_steps=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**记得保存模型哦**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save('cats_and_dogs_small_1.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAEICAYAAABPgw/pAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAgAElEQVR4nO3de3wU1fn48c/D3QCCAt64JKiohEsw5ItV8cJXRNQKXxQVjPcqimj9WUX5ahX1q7W2qKilKm1R0RikXsAqLa1WBeuNICA3QS4Bw52gCAlCIM/vjzNJNmE32U12s7uT5/167SvZmdmZZ3aSZ86cc+aMqCrGGGOSX6N4B2CMMSY6LKEbY4xPWEI3xhifsIRujDE+YQndGGN8whK6Mcb4hCV0nxKRxiKyW0S6RHPZeBKR40UkJv1sq65bRP4pItmxiENE7heR52v7eWNCsYSeILyEWvYqFZE9Ae+DJpbqqOoBVW2lquujuWyiEpH3ReSBINMvEZENItI4kvWp6iBVzYlCXANFJL/Kuv9PVW+u67pr2KaKyJ2x2oZJTJbQE4SXUFupaitgPXBRwLSDEouINKn/KBPay8BVQaZfBbyqqgfqOZ54ugbYAVxd3xu2v8v4soSeJETkERF5XURyRWQXcKWInCoin4vIDyKySUSeEZGm3vJNvFJamvf+VW/+30Vkl4h8JiJdI13Wm3++iKwUkZ0i8qyI/EdErg0Rdzgx3iQiq0TkexF5JuCzjUXkKREpFJE1wOBqvqK3gKNE5LSAz7cDLgCmeu+HiMhCEflRRNaLyP3VfN+flO1TTXGIyA0istz7rlaLyA3e9DbA34AuAVdbR3jH8qWAzw8TkaXed/RvETkxYF6BiPxKRBZ733euiDSvJu7WwMXALUC6iPSpMv9M73jsFJHvROQqb3qKt4/rvXlzRKR5sCsML6azvd8j+rv0PtPLu6LaISKbReRuEekoIsUi0jZguX7efDtJhEtV7ZVgLyAfGFhl2iPAPuAi3In4EOC/gFOAJsCxwErgVm/5JoACad77V4HtQBbQFHgdV3KNdNkjgF3AUG/er4AS4NoQ+xJOjDOBNkAarmQ50Jt/K7AU6AS0A+a4P9mQ39uLwPMB78cAeQHv/xvo4X1/Gd4+/tybd3zguoFPyvappji8Y3IsIN429gC9vXkDgfwgx/Il7/fuwG7vc02Be4EVQFNvfgHwOXCUt+2VwA3VfAfXeZ9pBPwdeCpgXldvW5d53317oI837wXgA+BooDHQ34snWPwFwNm1/LtsA2wBbgeaA4cC/bx5/wRuDNjOs4Hx2yuM3BHvAOwV5KCETuj/ruFzdwF/9X4PlqQDk90QYEktlr0emBswT4BNhEjoYcb4s4D5bwF3eb/PCUxeuNK2VrPus3EnhObe+y+A26pZ/g/A773fq0vokcbxLjDG+72mhP4Q8FrAvEbAZqC/974AGBEw/0ngD9Vs+yNggvf7VV7ybOK9v7/su6/ymcbAXqBHkHnhJPRI/i6vAuaFWC4b+Djgb2MbkBnt/y8/v6zKJbl8F/hGRE4Skfe8y9IfgYdxpa5QNgf8Xgy0qsWyxwTGoe6/ryDUSsKMMaxtAeuqiRfgY+BH4CIROQE4GcgNiOVUEflIRLaJyE7ghiCxBFNtHCLycxH5wqtC+AEYFOZ6y9Zdvj5VLcV9nx0DlgnruHlVZmcCZW0ub3vLllURdQZWB/nokUCzEPPCEcnfZagYyuLNENfbajCwVVW/qmVMDZIl9ORStavcC8AS4HhVPRR4AFdijqVNuKoHAEREqJx8qqpLjJtwCaBMtd0qvZPLVFxj4FXALFXdHrDINOBNoLOqtgH+HGYsIeMQkUOAN4DHgCNVtS2u6qBsvTV1b9wIpAasrxHu+90QRlxVXe1t9+8ishlYhUvU13jzvwOOC/K5Lbhqk2DzioCUgPia4Kp+AkXydxkqBlS1GHd8snHH75Vgy5nQLKEnt9bATqBIRLoDN9XDNt8FMkXkIu+f+3agQ4xinA78P6/BrB1wTxifmYor3V2P6/lSNZYdqvqTiPwMGBGFOJrjkuY24ICI/Bw4J2D+FqC911gZat1DRORsr+FwLK6N4oswYwt0NS559gl4XY67YjkMV5U2WFxXziYi0l5EMtT1AHoJmCgiR3mNwKd78XwDtBaR87z343F169Wp7pi/g2skvtVrdD1URPoFzJ+KO3YXevGaCFhCT2534kpfu3ClotdjvUFV3YJLEk8ChbjS1gJcHWy0Y3wO11C3GJiHKwnXFN8q4Etcon2vyuzRwGNeb4x7ccm0TnGo6g/AHbjqgh3AcNxJr2z+ElypM9/r9XFElXiX4r6f53AnhcHAEFUtCTM2AESkP676ZpKqbi57eXHlA5er6lpc4+U9XqxfAb28VdwBLAfme/N+A4iqfg/chjs5bvDmBVYBBRPymKvqTuBc4BLcyW4lcFbAZ+fg6s+/UNWQVXkmOPEaIIypFXE37GwEhqvq3HjHY5KfiMwBpqjqS/GOJdlYCd1ETEQGi0hbrz/0/bhui1/GOSzjA15VWE/gr/GOJRlZQje10R9Yg6siOA8YpqqhqlyMCYuI5AD/AG5X1aJ4x5OMrMrFGGN8wkroxhjjE3EbI6F9+/aalpYWr80bY0xSmj9//nZVDdpVOG4JPS0tjby8vHht3hhjkpKIhLxjusYqFxGZIiJbRWRJiPnijaa2SkS+FpHMugRrjDGmdsKpQ3+J6octPR/o5r1G4W6QMMYYU89qTOiqOgd3d1goQ4Gp6nwOtBWRo6MVoDHGmPBEow69I5VHWysbKW5T1QVFZBSuFE+XLgePs1RSUkJBQQE//fRTFMIysdKiRQs6depE06Y1DelhjKlP9dooqqqTgckAWVlZB3WALygooHXr1qSlpeEG8TOJRlUpLCykoKCArl271vwBY0y9iUY/9A1UHlq0tkN/8tNPP9GuXTtL5glMRGjXrp1dRRlTCzk5kJYGjRq5nzl1fgx5ZdFI6O8AV3u9XX4G7FTVg6pbwmXJPPHZMTKmQrhJOicHRo2CdetA1f0cNSq6Sb3GKhcRycU92qu9iBQQMB6yqj4PzMI9kmsV7mkq10UvPGOMSVxlSbq42L0vS9IA2dmVl73vvorlyhQXu+lVl62tcHq5jFTVo1W1qap2UtW/qOrzXjLH690yRlWPU9Veqpq0dwsVFhbSp08f+vTpw1FHHUXHjh3L3+/bty+sdVx33XWsWLGi2mUmTZpEThRPy1u2bKFJkyb8+c9/jto6jTE1qy5JV7V+ffB1hJpeG0k9lku066PatWvHwoULWbhwITfffDN33HFH+ftmzZoBrlGwtLQ05DpefPFFTjzxxGq3M2bMGLKjdUoGpk+fzqmnnkpubm7NCxvTgEWSM8JZNpIkHaRjX7XTayNpE3p91EeVWbVqFenp6WRnZ9OjRw82bdrEqFGjyMrKokePHjz88MPly/bv35+FCxeyf/9+2rZty7hx48jIyODUU09l69atAPz6179m4sSJ5cuPGzeOfv36ceKJJ/Lpp58CUFRUxCWXXEJ6ejrDhw8nKyuLhQsXBo0vNzeXiRMnsmbNGjZtqmi+eO+998jMzCQjI4NBgwYBsGvXLq655hp69+5N7969mTFjRvS/MGPqWTjJN5KcEe6ykSTpRx+FlJTK01JS3PSoUdW4vPr27atVLVu27KBpoaSmqrqvuvIrNTXsVVRr/Pjx+vvf/15VVb/99lsVEZ03b175/MLCQlVVLSkp0f79++vSpUtVVfX000/XBQsWaElJiQI6a9YsVVW944479LHHHlNV1fvuu0+feuqp8uXvvvtuVVWdOXOmnnfeeaqq+thjj+ktt9yiqqoLFy7URo0a6YIFCw6Kc+3atXriiSeqqurYsWN14sSJqqq6adMm7dy5s+bn51eK91e/+pXeeeedqqpaWlqqO3bsqNX3E8mxMiaWXn1VNSWlch5ISXHTA0WSM8JdNtxtBy6fmqoq4n6GWq46QJ6GyKtJW0Kvj/qoQMcddxxZWVnl73Nzc8nMzCQzM5Ply5ezbNmygz5zyCGHcP755wPQt29f8vPzg6774osvPmiZTz75hBEj3DOMMzIy6NGjR9DPTps2jcsvvxyAESNGlFe7fPbZZwwYMIDUVPdA+cMPPxyA999/nzFjxgCut8phhx0W9ndgTCIKtx47kpwR7rLZ2TB5MqSmgoj7OXly6EbO7GzIz4fSUvczijWvQBxHW6yrLl3cZVCw6bHQsmXL8t+//fZbnn76ab788kvatm3LlVdeGbRfdlm9O0Djxo3Zv39/0HU3b968xmVCyc3NZfv27bz8snvA/caNG1mzZk1E6zAmmYWbfCPJGZEsm50d/cRcW0lbQq+X+qgQfvzxR1q3bs2hhx7Kpk2bmD17dtS3cfrppzN9unso/eLFi4NeASxbtoz9+/ezYcMG8vPzyc/PZ+zYsUybNo3TTjuNDz/8kHXeX+WOHW44nnPPPZdJkyYBrrrt+++/j3rsxtSncOuxI8kZ8cwvdZG0CT3SS51oyszMJD09nZNOOomrr76a008/PerbuO2229iwYQPp6ek89NBDpKen06ZNm0rL5ObmMmzYsErTLrnkEnJzcznyyCN57rnnGDp0KBkZGeW9asaPH8+WLVvo2bMnffr0Ye7cuVGP3Zj6FG7yjSRnxDO/1EmoyvVYv+raKOp3JSUlumfPHlVVXblypaalpWlJSUmco6pgx8rEWiQNiNFobEwWVNMomrR16H63e/duzjnnHPbv34+q8sILL9CkiR0uk/xyclyD5fr1rlrk0UcPLvlGcgdm2bSELz3XA8sQCapt27bMnz8/3mEYE1XhJur6uE3ej5K2Dt0YkzjCvQMzFl0MTQVL6MaYOonkDsxIuhgGE6tuyX5hCd0YUyeRDFAViy6GpoIldGNMnURSPRKLLoamgiX0AAMGDDjoJqGJEycyevToaj/XqlUrwN2lOXz48KDLnH322eTlVT+y8MSJEykOKOpccMEF/PDDD+GEHpY+ffqUDydgTLREUj0SaV/wWN4m70eW0AOMHDmSadOmVZo2bdo0Ro4cGdbnjznmGN54441ab79qQp81axZt27at9foCLV++nAMHDjB37lyKioqisk7jf+E0dkZaPWKJOnYsoQcYPnw47733XvnDLPLz89m4cSNnnHFGeb/wzMxMevXqxcyZMw/6fH5+Pj179gRgz549jBgxgu7duzNs2DD27NlTvtzo0aPLh94dP348AM888wwbN25kwIABDBgwAIC0tDS2b98OwJNPPknPnj3p2bNn+dC7+fn5dO/enRtvvJEePXowaNCgStsJlJuby1VXXcWgQYMqxb5q1SoGDhxIRkYGmZmZrF69GoDHH3+cXr16kZGRwbhx4+r0vZrkFG5jp1WPJJBQdxzF+lXTnaK336561lnRfd1+e813YV144YU6Y8YMVXVD2JYNNVtSUqI7d+5UVdVt27bpcccdp6Wlpaqq2rJlS1V1Q9n26NFDVVWfeOIJve6661RVddGiRdq4cePy4XfLhrLdv3+/nnXWWbpo0SJVVU1NTdVt27aVx1L2Pi8vT3v27Km7d+/WXbt2aXp6un711Ve6du1abdy4cfmwupdeeqm+8sorQffrhBNO0HXr1uns2bP15z//efn0fv366VtvvaWqqnv27NGioiKdNWuWnnrqqVpUVFQp3kB2p6j/xXqIalM7+HH43FgJrHYJrG5RVe6991569+7NwIED2bBhA1u2bAm5njlz5nDllVcClD9Mosz06dPJzMzk5JNPZunSpUEH3gr0ySefMGzYMFq2bEmrVq24+OKLy8dg6dq1K3369AFCD9Gbl5dH+/bt6dKlC+eccw4LFixgx44d7Nq1iw0bNpSPB9OiRQtSUlJ4//33ue6660jxrqPLht41/hBun3HrC558EvZOUa9Wod4NHTqUO+64g6+++ori4mL69u0LQE5ODtu2bWP+/Pk0bdqUtLS0oEPm1mTt2rVMmDCBefPmcdhhh3HttdfWaj1lyobeBTf8brAql9zcXL755hvS0tIAN1rkm2++aQ2kDVAkt9TX9xDVpu6shF5Fq1atGDBgANdff32lxtCdO3dyxBFH0LRp00rD0oZy5pln8tprrwGwZMkSvv76a8Al05YtW9KmTRu2bNnC3//+9/LPtG7dml27dh20rjPOOIMZM2ZQXFxMUVERb7/9NmeccUZY+1NaWsr06dNZvHhx+RC7M2fOJDc3l9atW9OpU6fyx9Dt3buX4uJizj33XF588cXyBtqyoXdN8oukz7j1BU8+ltCDGDlyJIsWLaqU0LOzs8nLy6NXr15MnTqVk046qdp1jB49mt27d9O9e3ceeOCB8pJ+RkYGJ598MieddBJXXHFFpaF3R40axeDBg8sbRctkZmZy7bXX0q9fP0455RRuuOEGTj755LD2Ze7cuXTs2JFjjjmmfNqZZ57JsmXL2LRpE6+88grPPPMMvXv35rTTTmPz5s0MHjyYIUOGkJWVRZ8+fZgwYUJY2zKJL5JqFGvsTD7i6tjrX1ZWllbtl718+XK6d+8el3hMZOxYJae0tODVKKmprguhSXwiMl9Vs4LNsxK6MT4Riz7jJrlYQjfGB6zPuIEETOjxqgIy4bNjVH+iPSwt2J2afpZQCb1FixYUFhZawkhgqkphYSEtWrSIdyi+F4thaY2/JVSjaElJCQUFBXXql21ir0WLFnTq1ImmTZvGOxRfi6QB0xo7G47qGkUT6saipk2b0rVr13iHYUxCiHRY2sAbhsAaOxuihKpyMcZUiNWwtMa/LKEbk6BsWFoTKUvoxiQoK3WbSFlCNyYOwu2OaKVuE4mEahQ1piGIZMRDYyJhJXRjoiQWNwEZE4mwErqIDBaRFSKySkQOeh6ZiKSKyAci8rWIfCQinaIfqjGJy24CMomgxoQuIo2BScD5QDowUkTSqyw2AZiqqr2Bh4HHoh2oMYksklJ3JN0RjYlEOCX0fsAqVV2jqvuAacDQKsukA//2fv8wyHxjfC3Sm4BsxEMTC+Ek9I7AdwHvC7xpgRYBF3u/DwNai0i7qisSkVEikiciedu2batNvMbUu3Dqxu0mIJMIotUoehdwlogsAM4CNgAHqi6kqpNVNUtVszp06BClTRsTO+HWjdtNQCYRhJPQNwCdA9538qaVU9WNqnqxqp4M3OdN+yFqURoTJ+HWjVup2ySCGkdbFJEmwErgHFwinwdcoapLA5ZpD+xQ1VIReRQ4oKoPVLfeYKMtGpNoGjVyJfOqRFzp2pj6VqdH0KnqfuBWYDawHJiuqktF5GERGeItdjawQkRWAkcC1rxjfMF6pJhkEtadoqo6C5hVZdoDAb+/AbwR3dCMiT8bltYkE7tT1JhqWN24SSaW0I2vhHv7fSSsR4pJFjY4l/ENG/TKNHRWQje+YYNemYbOErrxjUhuv49F1Ywx8WYJ3fhGuF0MIxkZ0ZhkYgnd+Ea4t99b1YzxK0voxjfC7WJo45Ebv7JeLsZXsrNr7tHSpYurZgk23ZhkZiV00+DYeOTGryyhmwbH7v40fmVVLqZBCqdqxphkYyV0Y4zxCUvoxhjjE5bQTcKzuzqNCY/VoZuEZgNuGRM+K6GbhGZ3dRoTPkvoJqHZXZ3GhM8Suklo9kxPY8JnCd0kNLur05jwWUI3cRNO7xW7q9OY8FkvFxMXkfResbs6jQmPldBNXFjvFWOizxK6iQvrvWJM9FlCN3FhvVeMiT5L6Caqwr1N33qvGBN9ltBN1ETy8GXrvWJM9ImqxmXDWVlZmpeXF5dtm9hISwv+aLfUVMjPr+9ojPEnEZmvqlnB5lkJ3USNNXQaE1+W0E3UWEOnMfFlCd1EjTV0GhNfltBN1FhDpzHxZQndhCXc7ojZ2a4BtLTU/bRkbkz9sbFcTI3sqUHGJIewSugiMlhEVojIKhEZF2R+FxH5UEQWiMjXInJB9EM18WLjrhiTHGpM6CLSGJgEnA+kAyNFJL3KYr8GpqvqycAI4I/RDtTEj3VHNCY5hFNC7wesUtU1qroPmAYMrbKMAod6v7cBNkYvRBNv1h3RmOQQTkLvCHwX8L7AmxboQeBKESkAZgG3BVuRiIwSkTwRydu2bVstwjXxYN0RjUkO0erlMhJ4SVU7ARcAr4jIQetW1cmqmqWqWR06dIjSpk2sWXdEY5JDOAl9A9A54H0nb1qgXwDTAVT1M6AF0D4aAZrYCbcrIlh3RGOSQTgJfR7QTUS6ikgzXKPnO1WWWQ+cAyAi3XEJ3epUElgkIyMaY5JDjQldVfcDtwKzgeW43ixLReRhERniLXYncKOILAJygWs1XsM4mrBYV0Rj/MeGz22gGjVyJfOqRFy1ijEmMdnwueYg1hXRGP+xhN5AWVdEY/zHEroPhdN7xboiGuM/NjiXz0QykFZ2tiVwY/zESug+Y71XjGm4LKH7jA2kZUzDZQk9SYR7V6f1XjGm4bKEngQiuavTeq8Y03BZQk8CkdSLW+8VYxouu1M0CdhdncaYMnanaJKzenFjTDgsoScBqxc3xoTDEnoSsHpxY0w47E7RJGF3dRpjamIldGOM8QlL6MYY4xOW0I0xxicsoRtjjE9YQjfGGJ+whB5n4Q66ZYwxNbFui3EUycMojDGmJlZCjyN7GIW/bN0Kt90GF18M+/fHO5ro2LcP/vpXt28m8VlCjyN7GIU/7N4NDz0Exx0HkybB22/DSy/FO6q6KS2FadOge3e47DI45RRYvjzeUfnDsmWxO+FbQo8jvw66tXcvbNwY7yhir6QE/vhHl8gffBDOO88lvZ/9zL3fsyfeEdbOBx9Av34wciS0bAnPPef25bTTYM6ceEdXd7t2wdy54b0+/dRdpURDSYk78WdkwLPPRmedB1HVuLz69u2rfvXqq6qpqaoi7uerr4ZeLiVF1Q2O614pKaGXTwZLl6r26OH2Y+PGeEcTG6Wlqn/9q2q3bu6YnXmm6mefVcz/6CM3/fHHo7O97dtV58xx242lBQtUzzvPxd65s+rLL6vu3+/mrV2retJJqs2aqb72WmzjiJUDB1T//GfVDh0q/8/V9OrWTfW99+q27QULVPv0ceu74gp3TGsLyNMQedUSepRFmqTDTf7J4OWX3b526KDaqJHquHHxjij6PvpItV8/d1x79FD929+CJ9rzz1dt21Z1x466be/AAdX+/d32Bg50J8xoW7tW9cor3d/gYYepTpigumfPwcvt2OFOXqD629/G/gQTTf/5j2rfvi72005TnTlT9f33a3699prqiSe6z11wgeqKFZFtd+9e1QcfVG3SRPXII1Xffrvu+2IJvR6lpgY/y6emxjuy2Nm9W/Xaa91+nn22K5lfeqlqmzaqO3fGO7roWLBA9cIL3T526qQ6ZUpF6TWYhQtdgqzrSW3SJLfNK690J4jGjVV/+cu6nyhUXSnxjjtcqbtFC9V77ql5vT/9pDpihIvppptUS0rqHkcsFRSoZme7eI85RjUnJ/IT0d697iTXurVq06aqY8eG93e9YIFqRobbdna2amFh7fahKkvo9UgkeEIXiXdksbF0qWp6utu/Bx6oSHJffun2e8KE6Gxn50532fvBB6qff666eLHq6tWqmzer7tpVfXKtjZ9+Up09W/X221WPP97tS9u2rhqluDi8dWRnqx5yiOqGDbWLYd061VatXMm8tFR12zbVm292Vz/t26u+8ELk+33ggOqnn7pEfuihbl3XX6+6fn1k6xg3rqLUumtXZDEUF6t+/HH432Nt7Nmj+pvfqLZsqdq8ueq990YeZ1WbN7vvClxp+8UX3XdR1d69quPHV5TKZ8yo23arsoRejxpSCf2ll1wVyxFHqP7rXwfPHzBAtWNH9wdeV5dfHvx7DXy1aKHarp1qly6uauDmm1WffdadBDZvrrlktn696vPPqw4ZUlFt1qKFS1qTJkVewlq92pXoRo2KfH9LS121TUqK6po1lectWFBR9XHyya5+vTqBSbxzZ/e5Zs1UL7nEnRhr6/nn3QkhM7Pm9pL8fPcdXnihO8mVnQyiXcIvLXUJ9Nhj3Tb+53/ccYimL79U/dnP3Pr79XMFjDKxKpUHsoRej/zY0FlVYBXLgAGh/5n/8Q+3zIsv1m17n33m1nPbbaoffuhK6tOnuxPKpEmqv/udq6ccO1b1lltUr7rK1ZO2aVP5OLRrp3rGGS7RP/OMS/Qff+xKm716VSyXlqY6ZozbTl1Lkbfe6qpJIq17feUVF8vTTwefX1qqOm1aRYIeMaJyKTswiXfqVJHEL7pIdepU1R9+qP0+BXr3XVcK7tKlcv3+vn2uvWHsWHcFV/bdHnusO4733uvejxkTvbr4ZctUzz3XrTc9PXghI1oOHHDf49FHu+1dfbXqr3/tSuVHHRX9UnkgS+j1LBEaOteujc0l7ZIlFVUs48dXf8lfWqrau7dbPtilaThKS1VPPdX9k0R6yVxa6qo7/vlP1YkTVW+8UfX0013VSWCib9LE1f3//vcuKUWzsW/zZpfwLr00ss8cfrjb75qqVIqKXFVXixau4HD//bFP4lXl5bnj06aN+w7L2k/AXaGcc47qE0+ofvNN5e/2rrvcMhMn1j2GGTPcvrZt606C+/bVfZ3h+PFHVyBo1kzL2zpiUSoPZAm9gZk1yyWpbt3c5WE0lJaq/uUv7nL5iCNcD4BwvPqq+yv7299qt93p093n//Sn2n0+mLJE/69/ud4OsUp0Ze6/3+3DvHnhLX/ZZS5BRNKjZe1aV4VSX0m8qvx81e7d3faPPlr1F79Qfeut6hsPDxxQHTbMFQ7qUqLNzXVXQaecorplS+3XUxerV9dc9RUtltAbkE8+cUm3Vy93Od6kieojj9St0fDbb13DXE1VLMHs2+euUvr3j3y7P/2k2rWr25doN3rWp507XSPmwIE1L/v22+57/r//q922VqyovyReVXHxwaXwmhQVqf7Xf7mri7y8yLf5l7+4E8KZZ7rSckNgCb2BWLTIXXJ26+ZKKjt2VDQm9u/vSnGR2LvXnQyaN3c9IiZNql1iffppF8N//hPZ5yZMcJ+bPTvybSaap55y+1Jdve7337vSbe/e9VdlkKWZlB8AAA61SURBVAg2bXJ18EcfHVlvm2efdd/poEHuxNBQWEJvAFatcvWYHTu6y98ypaXu0rt1a5eUw63PnzOn4hL60ktr3/VO1TWiHn6463EQrm3bXD3s4MG1324i2bPHJa2+fUO3J9xwg+s1UpuSarJbvNj9ffbqFV4f78cfd3+bQ4e6K7mGpM4JHRgMrABWAeOCzH8KWOi9VgI/1LROS+jRs3Gj6z1w+OGh613XrHENgqA6cqQrDQZTWOjqP8u6Wr77bnRifOABd2m8fHl4y992m0tuS5ZEZ/uJ4KWX3Pf6+usHz3v/fTfv7rvrP65EMXu2qwsfPDh0d8bSUve3VNazpyFdyZSpU0IHGgOrgWOBZsAiIL2a5W8DptS0Xkvo0bFjhyvVtGyp+sUX1S9bUuLqZhs3dqXFjz6qmFda6rrKdejg5o8d60rW0bJ1q+uJ8Ytf1LzsihWu7v+mm6K3/USwf78bLqBbt8qJaPdu11Zw/PGxvdkmGUye7LLS6NEH18WXlqreeaebf911yd2uUhd1TeinArMD3v8v8L/VLP8pcG5N6/VzQi8tdWNA3HSTu9svVoqKXH/rpk0j63P7+ecueZTdmr5kietaBq6nwMKFsYn3lltcD4yaqm+GDnV3SG7eHJs44mnmTPc9P/98xbQ77nDTPv44fnElkrFj3ffx5JMV0w4ccEkeXN/+2naD9YO6JvThwJ8D3l8F/CHEsqnAJqBxiPmjgDwgr0uXLvW1//Vq1SrXSFPWx7llS/eHGe074vbudXcSNmrkRv6L1K5dFVUr4Oov//jH2JZ6Vq928d5zT+hlykYqfPTR2MURT6Wlrurr6KPdCfmzz9yJdfToeEeWOA4ccF0wRVyvn5IS1WuuqaiSSqZBwWKhPhP6PcCzNa1TfVhC37vXJaEWLVwD5B/+4BLYBRdo+S3a4fZDrsmBA64eHNwlal28/barr66voW4vv9ydPIJ1rTtwwN1G3rmzv6se5s51x+7BB91NV506+WcQs2gpKnK31R9ySMWQvg89ZMlctR6rXIAFwGk1rVOTNKGHugN07tyK25uHD69cpVA2dvbRR7vS6S9/Wbd/3tJSd7s0qD72WF32Jj7y8lzsv/vdwfOmTnXzXnml/uOqb2UjN0L0Gp79ZvPmirGRojXImx/UNaE3AdYAXQMaRXsEWe4kIB+QmtapSZjQg43Rcsgh7kabcHqE/PCDS8QibhjPN9+sXWmjrIX/rruSt7RyzjnuOwjsblZU5EqqWVkNo37066/dCT47O96RJLb168O/K7mhiEa3xQu87oirgfu8aQ8DQwKWeRD4bTjr0yRM6KFGUYTIeoR88UXFaGwXXRS60bS0VPW779wAV08+6eq7TzlFy1v4kzWZq7qxVcDd5VfmkUe0wTUMrlzZMLvdmbqpLqGLm1//srKyNC8vLy7bro1GjVz6DibSr3D/fnj6aXjgARBxzxns2ROWLnUPkC37+eOPFZ/p0AHS0+Gss+D++6FJk9rvS7ypQmYm/PST29etW6FbNxg40D1g2RgTmojMV9WsYPOSOC3Ury5dYN26g6enpka+riZN4M47YfhwGDMG7rqrYl6HDtCjB1x5pfvZo4dL5B061D72RCMCd98NV1wB774L773nkvvjj8c7MmOSm5XQw5STA9dfX/kJ4CkpMHkyZGfXfr2q8MknUFrqv8Rdnf37Xam8WTNYtQpuvdVdtRhjqlddCb1RfQeTrLKz4dhjK6o6UlPrnszBlVbPOMNVpTSUZA4VVykrV8Khh7rqJ2NM3TT4hJ6TA2lpro48Lc29D2b1avjmG1ffrQr5+XVP5g3d9de7toPHH4d27eIdjTHJr0HXoefkwKhRUFzs3q9b597Dwcn6pZdc0r/66noN0ddSUmDx4nhHYYx/NOgS+n33VSTzMsXFbnqgAwfg5Zdh0CDo1Kn+4jPGmEg06IS+fn140z/4AL77zlURGGNMomrQCb1Ll/CmT5kChx8OQ4bEPiZjjKmtBp3QH33U1eMGSklx08vs2AEzZrg69ebN6zc+Y4yJRINO6NnZruthaqrrPhisK2JuLuzda9UtxpjEZzcW1aBvX3fTz4IF8Y7EGGPsxqJaW7QIvvrKSufGmORgCb0aL77obk2/4op4R2KMMTWzhB7Cvn3w6qswdKjdxWiMSQ6W0EP429+gsNCqW4wxycMSeghTpkDHjnDuufGOxBhjwmMJPYiNG+Ef/4BrroHGjeMdjTHGhMcSehBTp7quitddF+9IjDEmfJbQq1B11S1nnAHHHx/vaIwxJnyW0Kv49FP49ltrDDXGJB/fJvScHDfIlkj1D66oasoUaNXKPe/TGGOSiS8fcJGTAzfeCHv2uPfVPbgi0O7d8PrrcPnlLqkbY0wy8WUJ/b77KpJ5meJiGDeu+s+98QYUFVl1izEmOfkyoa9bF3x6QYHrwRJqPLIpU+CEE+C002IXmzHGxIovE/qhhwaf3ry561s+cKB72nygb7+FuXNdV0WR2MdojDHR5ruEXljoxmGpekNQSgr86U/w/PMwfz706gUPP+zGOgd7CLQxJvn5LqE/9ZRL0o88cvCDK666Cm66Cb75Bi65BMaPh4wM+Pe/3UOgBw+GY46J9x4YY0zt+OoBF4WFroviBRe43io1mT0bRo+GtWvd+zfecIneGGMSVXUPuPBVt8Unn3S9VO6/P7zlzzsPlixxpfkFC+Cii2IbnzHGxJJvEnphITzzDFx6KfTsGf7nUlLgN7+JXVzGGFNffFOHHmnp3Bhj/MYXCb22pXNjjPETXyT0stL5Aw/EOxJjjImfpE/o27e70vlll0GPHvGOxhhj4ifpE7rVnRtjjBNWQheRwSKyQkRWiUjQIa5E5DIRWSYiS0XkteiGGdz27fDss1Y6N8YYCKPboog0BiYB5wIFwDwReUdVlwUs0w34X+B0Vf1eRI6IVcCBrHRujDEVwimh9wNWqeoaVd0HTAOGVlnmRmCSqn4PoKpboxvmwax0bowxlYWT0DsC3wW8L/CmBToBOEFE/iMin4vI4GArEpFRIpInInnbtm2rXcQeK50bY0xl0WoUbQJ0A84GRgJ/EpG2VRdS1cmqmqWqWR06dKj1xqx0bowxBwsnoW8AOge87+RNC1QAvKOqJaq6FliJS/Ax8cQT1u/cGGOqCiehzwO6iUhXEWkGjADeqbLMDFzpHBFpj6uCWRPFOMuVlc4vvxzS02OxBWOMSU41JnRV3Q/cCswGlgPTVXWpiDwsIkO8xWYDhSKyDPgQGKuqhbEI+Omn3fNBre7cGGMqS7rx0HfuhPfft3HLjTENU3XjoSfdnaJt2lgyN8aYYJIuoRtjjAnOEroxxviEJXRjjPEJS+jGGOMTltCNMcYnLKEbY4xPWEI3xhifsIRujDE+YQndGGN8whK6Mcb4hCV0Y4zxCUvoxhjjE5bQjTHGJyyhG2OMT1hCN8YYn7CEbowxPmEJ3RhjfMISujHG+ERSJfScHEhLg0aN3M+cnHhHZIwxiaNJvAMIV04OjBoFxcXu/bp17j1Adnb84jLGmESRNCX0++6rSOZliovddGOMMUmU0Nevj2y6McY0NEmT0Lt0iWy6McY0NEmT0B99FFJSKk9LSXHTjTHGJFFCz86GyZMhNRVE3M/Jk61B1BhjyiRNLxdwydsSuDHGBJc0JXRjjDHVs4RujDE+YQndGGN8whK6Mcb4hCV0Y4zxCVHV+GxYZBuwrsrk9sD2OIQTK37bH/DfPvltf8B/++S3/YG67VOqqnYINiNuCT0YEclT1ax4xxEtftsf8N8++W1/wH/75Lf9gdjtk1W5GGOMT1hCN8YYn0i0hD453gFEmd/2B/y3T37bH/DfPvltfyBG+5RQdejGGGNqL9FK6MYYY2rJEroxxvhEQiR0ERksIitEZJWIjIt3PNEgIvkislhEFopIXrzjqQ0RmSIiW0VkScC0w0XkXyLyrffzsHjGGIkQ+/OgiGzwjtNCEbkgnjFGQkQ6i8iHIrJMRJaKyO3e9GQ+RqH2KSmPk4i0EJEvRWSRtz8PedO7isgXXs57XUSaRWV78a5DF5HGwErgXKAAmAeMVNVlcQ2sjkQkH8hS1aS9IUJEzgR2A1NVtac37XfADlX9rXfyPUxV74lnnOEKsT8PArtVdUI8Y6sNETkaOFpVvxKR1sB84H+Aa0neYxRqny4jCY+TiAjQUlV3i0hT4BPgduBXwFuqOk1EngcWqepzdd1eIpTQ+wGrVHWNqu4DpgFD4xyTAVR1DrCjyuShwMve7y/j/tmSQoj9SVqquklVv/J+3wUsBzqS3Mco1D4lJXV2e2+bei8F/ht4w5setWOUCAm9I/BdwPsCkvgABlDgnyIyX0RGxTuYKDpSVTd5v28GjoxnMFFyq4h87VXJJE31RCARSQNOBr7AJ8eoyj5Bkh4nEWksIguBrcC/gNXAD6q631skajkvERK6X/VX1UzgfGCMd7nvK+rq65K93+tzwHFAH2AT8ER8w4mciLQC3gT+n6r+GDgvWY9RkH1K2uOkqgdUtQ/QCVcjcVKstpUICX0D0DngfSdvWlJT1Q3ez63A27gD6QdbvHrOsvrOrXGOp05UdYv3D1cK/IkkO05eveybQI6qvuVNTupjFGyfkv04AajqD8CHwKlAWxEpewRo1HJeIiT0eUA3r9W3GTACeCfOMdWJiLT0GnQQkZbAIGBJ9Z9KGu8A13i/XwPMjGMsdVaW+DzDSKLj5DW4/QVYrqpPBsxK2mMUap+S9TiJSAcRaev9fgiu88dyXGIf7i0WtWMU914uAF4XpIlAY2CKqj4a55DqRESOxZXKwT2I+7Vk3CcRyQXOxg31uQUYD8wApgNdcMMfX6aqSdHQGGJ/zsZdxiuQD9wUUP+c0ESkPzAXWAyUepPvxdU5J+sxCrVPI0nC4yQivXGNno1xBejpqvqwlyOmAYcDC4ArVXVvnbeXCAndGGNM3SVClYsxxpgosIRujDE+YQndGGN8whK6Mcb4hCV0Y4zxCUvoxhjjE5bQjTHGJ/4/ixs1LTqSeMsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "acc = history.history['acc']\n",
    "val_acc = history.history['val_acc']\n",
    "loss = history.history['loss']\n",
    "val_loss = history.history['val_loss']\n",
    "\n",
    "epochs = range(1, len(acc) + 1)\n",
    "\n",
    "plt.plot(epochs, acc, 'bo', label='Training Acc')\n",
    "plt.plot(epochs, val_acc, 'b', label='Validation Acc')\n",
    "plt.title('Training and Validation Accuracy')\n",
    "plt.legend()\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.plot(epochs, loss, 'bo', label='Training loss')\n",
    "plt.plot(epochs, val_loss, 'b', label='Validation loss')\n",
    "plt.title('Training and Validation Accuracy')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看出，在5轮开始就已经到达稳定，超过10轮就开始过拟合。\n",
    "\n",
    "样本过少导致容易出现过拟合，所以可以用一些方法增加样本的数量。\n",
    "\n",
    "图像具有特殊性：翻转、剪裁、缩放等操作后，目标仍然可识别，因此可以通过图像处理从原始样本集上得到更多样本数量。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "datagen = ImageDataGenerator(\n",
    "rotation_range=40,\n",
    "width_shift_range=0.2,\n",
    "height_shift_range=0.2,\n",
    "shear_range=0.2,\n",
    "zoom_range=0.2,\n",
    "horizontal_flip=True,\n",
    "fill_mode='nearest')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from keras.preprocessing import image\n",
    "\n",
    "fnames = [os.path.join(train_cats_dir, fname) for fname in os.listdir(train_cats_dir)]\n",
    "img_path = fnames[3]\n",
    "\n",
    "img = image.load_img(img_path, target_size=(150, 150))\n",
    "x = image.img_to_array(img)\n",
    "x = x.reshape((1,) + x.shape) # 形状转为(1, 150, 150, 3)\n",
    "\n",
    "i = 0\n",
    "for batch in datagen.flow(x, batch_size=1):\n",
    "    plt.figure(i)\n",
    "    imgplot = plt.imshow(image.array_to_img(batch[0]))\n",
    "    i += 1\n",
    "    if i % 4 == 0:\n",
    "        break\n",
    "        \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这些图像虽然都不一样，但是来自于同一个数据集转换的，所以进一步增加 dropout 层。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = models.Sequential()\n",
    "model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(150, 150, 3)))\n",
    "model.add(layers.MaxPooling2D((2, 2)))\n",
    "model.add(layers.Conv2D(64, (3, 3), activation='relu'))\n",
    "model.add(layers.MaxPooling2D((2, 2)))\n",
    "model.add(layers.Conv2D(128, (3, 3), activation='relu'))\n",
    "model.add(layers.MaxPooling2D((2, 2)))\n",
    "model.add(layers.Conv2D(128, (3, 3), activation='relu'))\n",
    "model.add(layers.MaxPooling2D((2, 2)))\n",
    "model.add(layers.Flatten())\n",
    "model.add(layers.Dropout(0.5))\n",
    "model.add(layers.Dense(512, activation='relu'))\n",
    "model.add(layers.Dense(1, activation='sigmoid'))\n",
    "\n",
    "model.compile(loss='binary_crossentropy',\n",
    "             optimizer=optimizers.RMSprop(lr=1e-4),\n",
    "             metrics=['acc'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 2000 images belonging to 2 classes.\n",
      "Found 1000 images belonging to 2 classes.\n",
      "Epoch 1/100\n",
      "100/100 [==============================] - 54s 536ms/step - loss: 0.6947 - acc: 0.5344 - val_loss: 0.6797 - val_acc: 0.5596\n",
      "Epoch 2/100\n",
      "100/100 [==============================] - 50s 504ms/step - loss: 0.6802 - acc: 0.5653 - val_loss: 0.6661 - val_acc: 0.5939\n",
      "Epoch 3/100\n",
      "100/100 [==============================] - 51s 511ms/step - loss: 0.6678 - acc: 0.5897 - val_loss: 0.6646 - val_acc: 0.5819\n",
      "Epoch 4/100\n",
      "100/100 [==============================] - 51s 508ms/step - loss: 0.6586 - acc: 0.6028 - val_loss: 0.6314 - val_acc: 0.6472\n",
      "Epoch 5/100\n",
      "100/100 [==============================] - 51s 512ms/step - loss: 0.6464 - acc: 0.6219 - val_loss: 0.6261 - val_acc: 0.6497\n",
      "Epoch 6/100\n",
      "100/100 [==============================] - 52s 519ms/step - loss: 0.6228 - acc: 0.6491 - val_loss: 0.6535 - val_acc: 0.5984\n",
      "Epoch 7/100\n",
      "100/100 [==============================] - 52s 521ms/step - loss: 0.6135 - acc: 0.6616 - val_loss: 0.6222 - val_acc: 0.6580\n",
      "Epoch 8/100\n",
      "100/100 [==============================] - 55s 553ms/step - loss: 0.6108 - acc: 0.6622 - val_loss: 0.5783 - val_acc: 0.6827\n",
      "Epoch 9/100\n",
      "100/100 [==============================] - 54s 539ms/step - loss: 0.6105 - acc: 0.6747 - val_loss: 0.5704 - val_acc: 0.6948\n",
      "Epoch 10/100\n",
      "100/100 [==============================] - 53s 535ms/step - loss: 0.5976 - acc: 0.6756 - val_loss: 0.5772 - val_acc: 0.6923\n",
      "Epoch 11/100\n",
      "100/100 [==============================] - 54s 542ms/step - loss: 0.5831 - acc: 0.6969 - val_loss: 0.5871 - val_acc: 0.6720\n",
      "Epoch 12/100\n",
      "100/100 [==============================] - 54s 537ms/step - loss: 0.5845 - acc: 0.6850 - val_loss: 0.5680 - val_acc: 0.7005\n",
      "Epoch 13/100\n",
      "100/100 [==============================] - 54s 537ms/step - loss: 0.5782 - acc: 0.6950 - val_loss: 0.5408 - val_acc: 0.7303\n",
      "Epoch 14/100\n",
      "100/100 [==============================] - 55s 547ms/step - loss: 0.5738 - acc: 0.7019 - val_loss: 0.5424 - val_acc: 0.7075\n",
      "Epoch 15/100\n",
      "100/100 [==============================] - 55s 548ms/step - loss: 0.5675 - acc: 0.7122 - val_loss: 0.5273 - val_acc: 0.7335\n",
      "Epoch 16/100\n",
      "100/100 [==============================] - 54s 539ms/step - loss: 0.5571 - acc: 0.7069 - val_loss: 0.5270 - val_acc: 0.7202\n",
      "Epoch 17/100\n",
      "100/100 [==============================] - 55s 554ms/step - loss: 0.5612 - acc: 0.7162 - val_loss: 0.5281 - val_acc: 0.7386\n",
      "Epoch 18/100\n",
      "100/100 [==============================] - 57s 570ms/step - loss: 0.5576 - acc: 0.7094 - val_loss: 0.5369 - val_acc: 0.7107\n",
      "Epoch 19/100\n",
      "100/100 [==============================] - 56s 563ms/step - loss: 0.5541 - acc: 0.7122 - val_loss: 0.5056 - val_acc: 0.7506\n",
      "Epoch 20/100\n",
      "100/100 [==============================] - 57s 574ms/step - loss: 0.5336 - acc: 0.7412 - val_loss: 0.5287 - val_acc: 0.7360\n",
      "Epoch 21/100\n",
      "100/100 [==============================] - 59s 590ms/step - loss: 0.5452 - acc: 0.7253 - val_loss: 0.5160 - val_acc: 0.7386\n",
      "Epoch 22/100\n",
      "100/100 [==============================] - 60s 599ms/step - loss: 0.5345 - acc: 0.7241 - val_loss: 0.4939 - val_acc: 0.7500\n",
      "Epoch 23/100\n",
      "100/100 [==============================] - 60s 597ms/step - loss: 0.5272 - acc: 0.7366 - val_loss: 0.4910 - val_acc: 0.7614\n",
      "Epoch 24/100\n",
      "100/100 [==============================] - 59s 590ms/step - loss: 0.5369 - acc: 0.7350 - val_loss: 0.5215 - val_acc: 0.7373\n",
      "Epoch 25/100\n",
      "100/100 [==============================] - 60s 600ms/step - loss: 0.5114 - acc: 0.7465 - val_loss: 0.4900 - val_acc: 0.7494\n",
      "Epoch 26/100\n",
      "100/100 [==============================] - 60s 597ms/step - loss: 0.5214 - acc: 0.7450 - val_loss: 0.4855 - val_acc: 0.7506\n",
      "Epoch 27/100\n",
      "100/100 [==============================] - 58s 584ms/step - loss: 0.5090 - acc: 0.7456 - val_loss: 0.5005 - val_acc: 0.7437\n",
      "Epoch 28/100\n",
      "100/100 [==============================] - 58s 581ms/step - loss: 0.5099 - acc: 0.7606 - val_loss: 0.5821 - val_acc: 0.7005\n",
      "Epoch 29/100\n",
      "100/100 [==============================] - 62s 619ms/step - loss: 0.4972 - acc: 0.7544 - val_loss: 0.4727 - val_acc: 0.7633\n",
      "Epoch 30/100\n",
      "100/100 [==============================] - 60s 601ms/step - loss: 0.5065 - acc: 0.7478 - val_loss: 0.4803 - val_acc: 0.7614\n",
      "Epoch 31/100\n",
      "100/100 [==============================] - 59s 592ms/step - loss: 0.5018 - acc: 0.7506 - val_loss: 0.4642 - val_acc: 0.7735\n",
      "Epoch 32/100\n",
      "100/100 [==============================] - 58s 576ms/step - loss: 0.4922 - acc: 0.7681 - val_loss: 0.4629 - val_acc: 0.7716\n",
      "Epoch 33/100\n",
      "100/100 [==============================] - 61s 606ms/step - loss: 0.5024 - acc: 0.7544 - val_loss: 0.4868 - val_acc: 0.7487\n",
      "Epoch 34/100\n",
      "100/100 [==============================] - 58s 583ms/step - loss: 0.4929 - acc: 0.7547 - val_loss: 0.4574 - val_acc: 0.7855\n",
      "Epoch 35/100\n",
      "100/100 [==============================] - 60s 603ms/step - loss: 0.4984 - acc: 0.7587 - val_loss: 0.4557 - val_acc: 0.7690\n",
      "Epoch 36/100\n",
      "100/100 [==============================] - 60s 602ms/step - loss: 0.4730 - acc: 0.7716 - val_loss: 0.5009 - val_acc: 0.7513\n",
      "Epoch 37/100\n",
      "100/100 [==============================] - 60s 597ms/step - loss: 0.4886 - acc: 0.7594 - val_loss: 0.4393 - val_acc: 0.7919\n",
      "Epoch 38/100\n",
      "100/100 [==============================] - 60s 595ms/step - loss: 0.4908 - acc: 0.7675 - val_loss: 0.4528 - val_acc: 0.7697\n",
      "Epoch 39/100\n",
      "100/100 [==============================] - 61s 608ms/step - loss: 0.4867 - acc: 0.7603 - val_loss: 0.4382 - val_acc: 0.8008\n",
      "Epoch 40/100\n",
      "100/100 [==============================] - 61s 614ms/step - loss: 0.4743 - acc: 0.7744 - val_loss: 0.5085 - val_acc: 0.7538\n",
      "Epoch 41/100\n",
      "100/100 [==============================] - 60s 597ms/step - loss: 0.4742 - acc: 0.7678 - val_loss: 0.4536 - val_acc: 0.7754\n",
      "Epoch 42/100\n",
      "100/100 [==============================] - 60s 600ms/step - loss: 0.4831 - acc: 0.7606 - val_loss: 0.4589 - val_acc: 0.7589\n",
      "Epoch 43/100\n",
      "100/100 [==============================] - 58s 583ms/step - loss: 0.4623 - acc: 0.7772 - val_loss: 0.4466 - val_acc: 0.7938\n",
      "Epoch 44/100\n",
      "100/100 [==============================] - 60s 596ms/step - loss: 0.4654 - acc: 0.7831 - val_loss: 0.4345 - val_acc: 0.8001\n",
      "Epoch 45/100\n",
      "100/100 [==============================] - 58s 583ms/step - loss: 0.4659 - acc: 0.7756 - val_loss: 0.4474 - val_acc: 0.7881\n",
      "Epoch 46/100\n",
      "100/100 [==============================] - 57s 567ms/step - loss: 0.4591 - acc: 0.7806 - val_loss: 0.4580 - val_acc: 0.7868\n",
      "Epoch 47/100\n",
      "100/100 [==============================] - 58s 581ms/step - loss: 0.4708 - acc: 0.7797 - val_loss: 0.4259 - val_acc: 0.7995\n",
      "Epoch 48/100\n",
      "100/100 [==============================] - 58s 579ms/step - loss: 0.4403 - acc: 0.7931 - val_loss: 0.4240 - val_acc: 0.8090\n",
      "Epoch 49/100\n",
      "100/100 [==============================] - 57s 570ms/step - loss: 0.4619 - acc: 0.7800 - val_loss: 0.4255 - val_acc: 0.8039\n",
      "Epoch 50/100\n",
      "100/100 [==============================] - 57s 573ms/step - loss: 0.4666 - acc: 0.7772 - val_loss: 0.4598 - val_acc: 0.7671\n",
      "Epoch 51/100\n",
      "100/100 [==============================] - 57s 567ms/step - loss: 0.4402 - acc: 0.7875 - val_loss: 0.4449 - val_acc: 0.7773\n",
      "Epoch 52/100\n",
      "100/100 [==============================] - 57s 567ms/step - loss: 0.4324 - acc: 0.8034 - val_loss: 0.4213 - val_acc: 0.8039\n",
      "Epoch 53/100\n",
      "100/100 [==============================] - 57s 570ms/step - loss: 0.4405 - acc: 0.7891 - val_loss: 0.4386 - val_acc: 0.7931\n",
      "Epoch 54/100\n",
      "100/100 [==============================] - 57s 567ms/step - loss: 0.4285 - acc: 0.7991 - val_loss: 0.4522 - val_acc: 0.7887\n",
      "Epoch 55/100\n",
      "100/100 [==============================] - 57s 565ms/step - loss: 0.4489 - acc: 0.7872 - val_loss: 0.4556 - val_acc: 0.7722\n",
      "Epoch 56/100\n",
      "100/100 [==============================] - 57s 570ms/step - loss: 0.4313 - acc: 0.8038 - val_loss: 0.4226 - val_acc: 0.8008\n",
      "Epoch 57/100\n",
      "100/100 [==============================] - 56s 556ms/step - loss: 0.4357 - acc: 0.7969 - val_loss: 0.3858 - val_acc: 0.8280\n",
      "Epoch 58/100\n",
      "100/100 [==============================] - 56s 565ms/step - loss: 0.4458 - acc: 0.8003 - val_loss: 0.4146 - val_acc: 0.8001\n",
      "Epoch 59/100\n",
      "100/100 [==============================] - 55s 552ms/step - loss: 0.4323 - acc: 0.7994 - val_loss: 0.4027 - val_acc: 0.8096\n",
      "Epoch 60/100\n",
      "100/100 [==============================] - 57s 565ms/step - loss: 0.4297 - acc: 0.7931 - val_loss: 0.4260 - val_acc: 0.8122\n",
      "Epoch 61/100\n",
      "100/100 [==============================] - 57s 565ms/step - loss: 0.4233 - acc: 0.8031 - val_loss: 0.4219 - val_acc: 0.8154\n",
      "Epoch 62/100\n",
      "100/100 [==============================] - 56s 560ms/step - loss: 0.4077 - acc: 0.8187 - val_loss: 0.4739 - val_acc: 0.7735\n",
      "Epoch 63/100\n",
      "100/100 [==============================] - 56s 560ms/step - loss: 0.4210 - acc: 0.8034 - val_loss: 0.4139 - val_acc: 0.8115\n",
      "Epoch 64/100\n",
      "100/100 [==============================] - 57s 566ms/step - loss: 0.4269 - acc: 0.7988 - val_loss: 0.4367 - val_acc: 0.7938\n",
      "Epoch 65/100\n",
      "100/100 [==============================] - 56s 561ms/step - loss: 0.4047 - acc: 0.8103 - val_loss: 0.4615 - val_acc: 0.7709\n",
      "Epoch 66/100\n",
      "100/100 [==============================] - 56s 559ms/step - loss: 0.4042 - acc: 0.8131 - val_loss: 0.4088 - val_acc: 0.8027\n",
      "Epoch 67/100\n",
      "100/100 [==============================] - 57s 570ms/step - loss: 0.4184 - acc: 0.8081 - val_loss: 0.4473 - val_acc: 0.7754\n",
      "Epoch 68/100\n",
      "100/100 [==============================] - 57s 566ms/step - loss: 0.3976 - acc: 0.8191 - val_loss: 0.4135 - val_acc: 0.8065\n",
      "Epoch 69/100\n",
      "100/100 [==============================] - 56s 565ms/step - loss: 0.4160 - acc: 0.8125 - val_loss: 0.3930 - val_acc: 0.8147\n",
      "Epoch 70/100\n",
      "100/100 [==============================] - 56s 560ms/step - loss: 0.4063 - acc: 0.8137 - val_loss: 0.4481 - val_acc: 0.8033\n",
      "Epoch 71/100\n",
      "100/100 [==============================] - 56s 560ms/step - loss: 0.3970 - acc: 0.8166 - val_loss: 0.4246 - val_acc: 0.7982\n",
      "Epoch 72/100\n",
      "100/100 [==============================] - 57s 567ms/step - loss: 0.3946 - acc: 0.8241 - val_loss: 0.4090 - val_acc: 0.8058\n",
      "Epoch 73/100\n",
      "100/100 [==============================] - 56s 561ms/step - loss: 0.4035 - acc: 0.8134 - val_loss: 0.3968 - val_acc: 0.8293\n",
      "Epoch 74/100\n",
      "100/100 [==============================] - 56s 565ms/step - loss: 0.4009 - acc: 0.8234 - val_loss: 0.4194 - val_acc: 0.8135\n",
      "Epoch 75/100\n",
      "100/100 [==============================] - 57s 569ms/step - loss: 0.4001 - acc: 0.8241 - val_loss: 0.4070 - val_acc: 0.8223\n",
      "Epoch 76/100\n",
      "100/100 [==============================] - 57s 566ms/step - loss: 0.3878 - acc: 0.8169 - val_loss: 0.3883 - val_acc: 0.8325\n",
      "Epoch 77/100\n",
      "100/100 [==============================] - 57s 569ms/step - loss: 0.3970 - acc: 0.8206 - val_loss: 0.4306 - val_acc: 0.8077\n",
      "Epoch 78/100\n",
      "100/100 [==============================] - 56s 561ms/step - loss: 0.3882 - acc: 0.8178 - val_loss: 0.4352 - val_acc: 0.8122\n",
      "Epoch 79/100\n",
      "100/100 [==============================] - 57s 566ms/step - loss: 0.3831 - acc: 0.8294 - val_loss: 0.4087 - val_acc: 0.8147\n",
      "Epoch 80/100\n",
      "100/100 [==============================] - 57s 573ms/step - loss: 0.3718 - acc: 0.8287 - val_loss: 0.4747 - val_acc: 0.7931\n",
      "Epoch 81/100\n",
      "100/100 [==============================] - 57s 569ms/step - loss: 0.3709 - acc: 0.8362 - val_loss: 0.3825 - val_acc: 0.8236\n",
      "Epoch 82/100\n",
      "100/100 [==============================] - 57s 571ms/step - loss: 0.3930 - acc: 0.8284 - val_loss: 0.4266 - val_acc: 0.8185\n",
      "Epoch 83/100\n",
      "100/100 [==============================] - 57s 568ms/step - loss: 0.3852 - acc: 0.8247 - val_loss: 0.4284 - val_acc: 0.8084\n",
      "Epoch 84/100\n",
      "100/100 [==============================] - 57s 571ms/step - loss: 0.3564 - acc: 0.8394 - val_loss: 0.3787 - val_acc: 0.8407\n",
      "Epoch 85/100\n",
      "100/100 [==============================] - 57s 572ms/step - loss: 0.3731 - acc: 0.8369 - val_loss: 0.3754 - val_acc: 0.8325\n",
      "Epoch 86/100\n",
      "100/100 [==============================] - 57s 570ms/step - loss: 0.3703 - acc: 0.8363 - val_loss: 0.4740 - val_acc: 0.7779\n",
      "Epoch 87/100\n",
      "100/100 [==============================] - 57s 575ms/step - loss: 0.3689 - acc: 0.8403 - val_loss: 0.4231 - val_acc: 0.8141\n",
      "Epoch 88/100\n",
      "100/100 [==============================] - 58s 576ms/step - loss: 0.3667 - acc: 0.8416 - val_loss: 0.3836 - val_acc: 0.8357\n",
      "Epoch 89/100\n",
      "100/100 [==============================] - 57s 574ms/step - loss: 0.3757 - acc: 0.8266 - val_loss: 0.4126 - val_acc: 0.8211\n",
      "Epoch 90/100\n",
      "100/100 [==============================] - 57s 571ms/step - loss: 0.3708 - acc: 0.8341 - val_loss: 0.3886 - val_acc: 0.8255\n",
      "Epoch 91/100\n",
      "100/100 [==============================] - 61s 606ms/step - loss: 0.3602 - acc: 0.8412 - val_loss: 0.6495 - val_acc: 0.7392\n",
      "Epoch 92/100\n",
      "100/100 [==============================] - 58s 584ms/step - loss: 0.3679 - acc: 0.8372 - val_loss: 0.4485 - val_acc: 0.7938\n",
      "Epoch 93/100\n",
      "100/100 [==============================] - 58s 577ms/step - loss: 0.3582 - acc: 0.8409 - val_loss: 0.5355 - val_acc: 0.7576\n",
      "Epoch 94/100\n",
      "100/100 [==============================] - 58s 578ms/step - loss: 0.3555 - acc: 0.8419 - val_loss: 0.5038 - val_acc: 0.7887\n",
      "Epoch 95/100\n",
      "100/100 [==============================] - 57s 571ms/step - loss: 0.3593 - acc: 0.8459 - val_loss: 0.3821 - val_acc: 0.8338\n",
      "Epoch 96/100\n",
      "100/100 [==============================] - 58s 582ms/step - loss: 0.3621 - acc: 0.8444 - val_loss: 0.4012 - val_acc: 0.8135\n",
      "Epoch 97/100\n",
      "100/100 [==============================] - 57s 570ms/step - loss: 0.3496 - acc: 0.8447 - val_loss: 0.3889 - val_acc: 0.8280\n",
      "Epoch 98/100\n",
      "100/100 [==============================] - 58s 577ms/step - loss: 0.3590 - acc: 0.8450 - val_loss: 0.3796 - val_acc: 0.8458\n",
      "Epoch 99/100\n",
      "100/100 [==============================] - 58s 580ms/step - loss: 0.3415 - acc: 0.8547 - val_loss: 0.4217 - val_acc: 0.8154\n",
      "Epoch 100/100\n",
      "100/100 [==============================] - 57s 573ms/step - loss: 0.3485 - acc: 0.8478 - val_loss: 0.4009 - val_acc: 0.8185\n"
     ]
    }
   ],
   "source": [
    "train_datagen = ImageDataGenerator(\n",
    "    rescale=1./255,\n",
    "    rotation_range=40,\n",
    "    width_shift_range=0.2,\n",
    "    height_shift_range=0.2,\n",
    "    shear_range=0.2,\n",
    "    zoom_range=0.2,\n",
    "    horizontal_flip=True,\n",
    ")\n",
    "\n",
    "test_datagen = ImageDataGenerator(rescale=1./255)\n",
    "\n",
    "train_generator = train_datagen.flow_from_directory(\n",
    "    train_dir,\n",
    "    target_size=(150, 150),\n",
    "    batch_size=32,\n",
    "    class_mode='binary'\n",
    ")\n",
    "\n",
    "validation_generator = test_datagen.flow_from_directory(\n",
    "    validation_dir,\n",
    "    target_size=(150, 150),\n",
    "    batch_size=32,\n",
    "    class_mode='binary'\n",
    ")\n",
    "\n",
    "history = model.fit_generator(\n",
    "    train_generator,\n",
    "    steps_per_epoch=100,\n",
    "    epochs=100,\n",
    "    validation_data=validation_generator,\n",
    "    validation_steps=50\n",
    ")\n",
    "\n",
    "model.save('cats_and_dogs_small_2.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "acc = history.history['acc']\n",
    "val_acc = history.history['val_acc']\n",
    "loss = history.history['loss']\n",
    "val_loss = history.history['val_loss']\n",
    "\n",
    "epochs = range(1, len(acc) + 1)\n",
    "\n",
    "plt.plot(epochs, acc, 'bo', label='Training Acc')\n",
    "plt.plot(epochs, val_acc, 'b', label='Validation Acc')\n",
    "plt.title('Training and Validation Accuracy')\n",
    "plt.legend()\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.plot(epochs, loss, 'bo', label='Training loss')\n",
    "plt.plot(epochs, val_loss, 'b', label='Validation loss')\n",
    "plt.title('Training and Validation Accuracy')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上图中可以发现，不再过拟合，验证精度随着训练精度一起上升。最高可以提高到87%。但是**从头开始训练**自己的模型想再提高有局限性，需要使用**与训练模型**。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里使用 VGG16 架构，架构较老，但是概念简单。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
